Nan Lu

11 papers · 2019–2026 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (17) 🐣 Hot Topic Early Bird 💎 Century Club · Bronze

🔥 Unstoppable · Bronze

Venues

ACML (2) ICLR (2) ICML (2) NeurIPS (2) ACL (1) AISTATS (1) JMLR (1)

Top co-authors

Masashi Sugiyama (9) Gang Niu (7) Tianyi Zhang (3) Tongtong Fang (2) Ye Wang (1) Laura Iacovissi (1) Bo An (1) Ruixin Wei (1) Senlin Shu (1) Yuting Tang (1)

Research topics

Machine Learning (10) Learning Types · Machine Learning (10) Core Methods (5) Optimization & Theory (5) Application Areas (4) Artificial Intelligence (1) Deep Learning (1) Speech & Audio (1) Learning Paradigms (1) Learning Types · Deep Learning (1) Synthesis (1) Techniques (1)

Keywords

unlabeled data (4) class prior (4) semi-supervised learning (3) domain adaptation (3) weakly supervised learning (3) importance weighting (3) empirical risk minimization (3) binary classification (2) distribution shift (2) binary classifier (2) supervised classification (1) multi-class classification (1) density ratio estimation (1) noisy label learning (1) pairwise comparison (1) covariate shift (1) support vector machine (1) generalization error bound (1) deep learning (1) risk estimation (1)

Papers

Corruptions of Supervised Learning Problems: Typology and Mitigations JMLR 2026 TED-TTS: Training-Free Intra-Utterance Emotion and Duration Control for Text-to-Speech Synthesis ACL 2026 Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems NeurIPS 2023 Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients ICLR 2022 Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization ACML 2022 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification ICML 2021 Pointwise Binary Classification with Pairwise Confidence Comparisons ICML 2021 A One-step Approach to Covariate Shift Adaptation ACML 2020 Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach AISTATS 2020 Rethinking Importance Weighting for Deep Learning under Distribution Shift NeurIPS 2020 On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data ICLR 2019